1. Field of the Invention
The present invention relates generally to data storage and retrieval systems. More specifically, a method is disclosed for adapting the properties of an analog equalization filter used in the read channel of a magnetic disc storage system. In one embodiment, an input from a magnetoresistive head is equalized using an adaptive filter that adapts to the changing properties of a magnetic disc reading system so that errors in the output of the system are minimized.
2. Description of the Related Art
As recording density and speed have increased for magnetic disc storage systems, more exact equalization of the signals read from magnetic storage discs has become necessary. Adaptive equalization has become an important technique that allows equalization to be tuned for the specific properties of a given magnetic storage and retrieval set of hardware. For example, as the fly height of the magnetic head used to read a magnetic disc changes over time, the properties of an adaptive equalization filter may be adapted to maintain the optimization of the equalization filter for the specific hardware associated with the equalization filter. Also, the properties of a magnetic storage disk may change over time, making it necessary to adapt the parameters of the equalization filter to maintain optimal system performance.
It should be appreciated that the adaptive equalization filter technique disclosed herein is applicable to many data storage and retrieval systems, including data storage systems using Partial Response signaling. In addition, it should also be noted that adaptive filter technique may also be used to improve equalization for a signal received from a communication channel. In one embodiment, the technique is used in an EPRML system for storing and retrieving information from a magnetic storage disk. For the purpose of clarity, that system is referred to throughout this description. It should be understood, however that the techniques described apply other data storage and data communication systems.
FIG. 1 is a block diagram illustrating a magnetic storage channel and equalization filter for a PRML system. A signal a(n) is the media code signal at time nT, where T is the channel symbol duration. The signal a(n) over time represents the sequence of binary symbols which are stored on and recovered from a magnetic storage channel 100. Magnetic storage channel 100 is also referred to as the media channel. If the system works ideally, then, after passing through magnetic storage channel 100 and an equalization filter 102, a(n) is transformed into x(n). x(n) is the ideal output when the channel is read for a given system. x(n) is determined by a transfer function that describes the intersymbol interference of the reading and writing system. In a real system, the output of the equalization filter is actually y(n), where y(n) differs from x(n) by an error amount. This error is described in further detail below. It should be noted that the read signal from the magnetic storage channel may be digitized either before or after equalization filter 102.
For a PRML system where the signal is equalized to the Class IV Partial Response and the maximum-likelihood (ML) detection is preformed with a Viterbi detector as described in Lee and Messerschmitt, Digital Communication, Kluwer Academic Press 1994, which is herein incorporated by reference for all purposes, the equalized noise-free sampled output is given by the difference equation:
x(n)=a(n)xe2x88x92a(nxe2x88x922)xe2x80x83xe2x80x83Equ. 1
where x(n) is the output sample value at time nT, a(n) is the media code at time nT, and T is the channel symbol duration. The input symbols a(n) are picked from the binary set {0,1}. The noise-free output sample values are ternary, namely, 0, +1, or xe2x88x921. Equ. 1 is referred to as the partial response polynomial and may also be represented as the transfer function 1xe2x88x92D2 where D represents 1 unit time delay. 1xe2x88x92D2 is the standard PRML transfer function that describes the result of the prescribed intersymbol interference that characterizes PRML. The inverse of 1xe2x88x92D2 is represented as 1/(1xe2x88x92D2).
Other transfer functions exist for other systems which implement different partial response targets. The transfer function for EPRML when the signal is equalized to the Extended Class IV Partial Response is 1+D1xe2x88x92D2xe2x88x92D3 and is derived according to the extended partial response polynomial:
x(n)=a(n)+a(nxe2x88x921)xe2x88x92a(nxe2x88x922)xe2x88x92a(nxe2x88x923)xe2x80x83xe2x80x83Equ. 2
As mentioned above, the output of the equalization filter in a real system does not match this x(n) exactly. One cause of errors is a mismatch between the transfer function of the equalization filter and the physical characteristics of the media channel. This causes distortion in x(n), resulting in actual output signal y(n) that differs from x(n) by an error amount, e(n). As noted above, it has become necessary in many systems to provide some sort of adaptive equalization to account for both variations in a manufactured disc drive within manufacturing tolerances and variations of individual disc drives over time as wear occurs or ambient environmental conditions change.
FIG. 2 is a block diagram illustrating a read channel processing system for a magnetic storage system that includes adaptive equalization as it is currently practiced. A magnetoresistive head 200 flies above and reads a signal from a magnetic storage disc 201. The signal from the magnetoresistive head 200 is input to a variable gain amplifier 204 that amplifies the analog signal prior to equalization and conversion of the signal to a digital signal.
The output of the variable gain amplifier 204 is fed to an analog equalization filter 206. Equalization of the signal read from the magnetic disc is performed according to the specific read/write scheme used to record data on the disc. As mentioned above, a number of coding schemes have been developed for encoding data onto magnetic discs in a manner that controls the inter-symbol interference of data located in adjacent storage locations. Some of the systems devised include Partial Response Maximum Likelihood (PRML), extended PRML (EPRML) and a specific version of EPRML used in one embodiment referred to as EPR4. Once the analog signal is equalized, it is input to an analog-to-digital (ADC) converter 208.
As mentioned above adaptive equalization is required in some systems to maintain acceptable performance. Therefore, the digital signal output from ADC 208 is input to a digital finite impulse response (FIR) filter that processes the digital signal prior to inputting the signal to a Viterbi detector 212. The digital FIR filter receives feedback from Viterbi detector 212 for the purpose of adjusting the filter parameters of the digital FIR filter. In this manner, the filter parameters of the digital FIR filter are optimized for the specific properties of the magnetic disc reading system that exists at the time that a magnetic disc is being read.
This adaptive equalization filter architecture is effective to optimize the equalization and maintain system performance as the hardware characteristics of the system vary over time. However, the inclusion of the digital FIR filter 210 in the system adds both complexity and cost. Generally, it is believed that this added costs and complexity is necessary to provide effective adaptive equalization that maintains the performance of the system. What is needed is a simpler and less costly method of providing adaptive equalization in such a system while still maintaining the performance of the system and keeping a low data error rate.
Accordingly, a system and method is disclosed for adapting an analog equalization filter prior to digitizing the read channel signal in a magnetic disc read channel system. The method disclosed adapts the boost of an analog equalization filter. It is shown that such adaptation is sufficient to maintain the performance of the read channel system without including a digital FIR filter. This result enables the system to be more simple and less costly since the need for a digital FIR filter component may be eliminated entirely. Several methods are disclosed for adapting the boost of the analog equalization filter based on an error signal derived form the output of a Viterbi detector and the raw output from an ADC.
In one embodiment, a method of adaptively equalizing a read signal from a data storage media is disclosed. An analog output signal is equalized by reading the data storage media using an analog equalization filter. The analog output of the analog equalization filter is converted to a raw digital output signal. The raw digital output signal is processed to detect and correct an error in the raw digital output signal. The error is detected and an adjustment is made to the boost of the analog equalization filter according to the error detected.
In another embodiment, a system for adaptively equalizing a read signal from a data storage media is disclosed. The system includes an adaptive analog equalization filter having an adjustable boost. An analog to digital converter converts the output of the adaptive analog equalization filter to a raw digital signal. A Viterbi detector for detecting errors in the raw digital signal has an output that outputs a corrected signal. An adaptation processor compares the raw digital signal to the corrected signal that is output from the Viterbi detector and generates a boost adjustment signal that is input to the adaptive analog equalization filter. Thus, the adaptive analog equalization filter is adjusted to minimize the errors detected by the Viterbi detector.